1. Field of the Invention
The present invention relates generally to wireless communication systems and, more particularly, to methods and receiver architectures for channel estimation in client terminals of broadband wireless communication systems.
2. Description of Related Art
Typically, as shown in FIG. 1, a wireless communication system comprises elements such as client terminals or mobile stations and base stations. Other network devices may also be employed, such as a mobile switching center (not shown). As illustrated, the communication path from the base station (BS) to the client terminal or mobile station (MS) is referred to herein as a downlink (DL) direction, and the communication path from the client terminal to the base station is referred to herein as an uplink (UL) direction. In some wireless communication systems, the MS communicates with the BS in both the DL and UL directions. For instance, such communication is carried out in cellular telephone systems. In other wireless communication systems, the client terminal communicates with the base stations in only one direction, usually the DL. Such DL communication may occur in applications such as paging.
As shown in FIG. 2, client terminal/MS 12 typically contains a baseband subsystem 16 and a radio frequency (RF) subsystem 18. Memory 20, such as an external memory, is shown connected to the baseband subsystem 16. The baseband subsystem 16 normally includes a micro controller unit (MCU) 22, a signal processing unit (SPU) 24, data converters 26, peripherals 28, power management 30, and memory 32 as shown in FIG. 3. The SPU may be a digital signal processor (DSP), hardware (HW) accelerators, co-processors or a combination of the above. Normally the overall control of the baseband subsystem 16 is performed by software running on the MCU 22 and the processing of signals is done by the SPU 24.
Analog to digital converters (ADCs) convert a received analog signals into digital for the baseband system to process them. Similarly, digital to analog converters (DACs) convert the processed baseband digital signals into analog for transmission. The ADCs and DACs are collectively referred to herein as “data converters” 26. The data converters 26 can either be part of the baseband subsystem 16 or the RF subsystem 18. Depending on the location of the data converters 26, the interface between the two subsystems will be different. The location of the data converters 26 does not alter the overall function of the client terminal.
An RF subsystem 18 normally includes a receiver section and a transmitter section. An example RF subsystem 18 for a time division duplex (TDD) communication system is shown in FIG. 4. The receiver section normally may include one or more receivers. The receiver 34 performs the task of converting the signal from RF to baseband. Each receiver may include mixers 36, filters 38, low noise amplifiers (LNAs) 40 and variable gain amplifiers (VGAs) 42. The transmitter section may include one or more transmitters. The transmitter 44 performs the task of converting the baseband signal up to the RF. Each transmitter may include mixers 46, filters 48, and gain control stage 50. In some architectures of the RF subsystem, some of the components may be shared between the receiver section and the transmitter section. As shown, the receiver section 34 and the transmitter section 44 are coupled to an antenna 54 via a transmit/receive switch 56. Synthesizer 58 is also shown as coupling to the receiver section 34 and the transmitter section 44. In an RF subsystem for a Frequency Division Duplex (FDD) communication system, the transmitter section and the receiver section may have separate synthesizers. The transmitter and the receiver in an RF subsystem for an FDD communication system may be coupled to the antenna using a duplexer.
The input of each receiver is normally coupled with an antenna and the output of the receiver is normally coupled with ADC. The antenna, receiver, ADC and other related components are collectively referred herein as “receive chain.” FIG. 5 illustrates the elements of a receive chain.
For coherent detection at the receiver of a wireless communication system, it is necessary to know the precise reference phase and in some cases the reference amplitude of the received signal. To facilitate this at the receiver, the transmitter of a wireless communication system often embeds reference information such as pilots, training symbols, etc., in the transmitted signal.
Normally in wireless communication systems the propagation channel introduces random phase and amplitude variations to the signal. The reference information is used at the receiver to achieve accurate estimation of the propagation channel between the transmitter and the receiver and the estimation process is referred herein as channel estimation. In broadband wireless communication systems, normally the RF channel bandwidth is wide, e.g., on the order of 10 MHz to 20 MHz. The large delay spread of propagation channels in mobile communication systems leads to frequency selective fading within the RF channel, i.e., different parts of the channel bandwidth experience different fading. Furthermore, the channel conditions between the transmitter and the receiver for mobile wireless communications systems can vary rapidly because of the mobility of the client terminals and the changes in the environment.
Many different methods are used for channel estimation and some of the commonly used methods are Minimum Mean Square Error (MMSE), Wiener-Filtering, etc. Most of these methods use available channel estimates based on reference information as inputs and produce improved channel estimates for the entire channel bandwidth of interest. Normally, the available input channel estimates are obtained from the reference information or from the previously demodulated information.
Many of the commonly used channel estimation methods require knowledge of the channel statistics. Two commonly used channel statistics are the propagation channel correlation over time and channel bandwidth and the Signal-to-Interference and Noise Ratio (SINR) of the received signal. Some channel estimation methods jointly use these two channel statistics in a manner that minimizes the channel estimation error. When the SINR of the received signal is high, the input channel estimates may be considered more reliable and therefore more emphasis is given to the input channel estimates by the channel estimation method. When the SINR is low, the input channel estimates are likely to be less reliable and therefore more averaging is performed among adjacent input channel estimates in accordance with the propagation channel correlation. The channel estimation methods dynamically vary the degree of averaging versus interpolation. When the SINR is high, the channel estimation performs more interpolation according to channel correlation and when the SINR is low the channel estimation performs more averaging.
In general the channel statistics may not be known a priori. However, under typical operating conditions for a particular wireless communication system, some a priori information may be used to get a first order approximation of the channel statistics. Based on extensive field measurements and laboratory experiments, the propagation of signals in mobile wireless communication environment may be described using a few channel models. For example, a propagation channel model called “Pedestrian” has been defined by the International Telecommunication Union (ITU) to model the channel behavior under pedestrian mobile conditions. Similarly, propagation channel models called “Vehicular” and “Indoor” have been defined by the ITU to model the channel behavior under vehicular mobile and indoor usage conditions respectively. For all these ITU propagation channel models there are two variants defined, namely A and B. These channel models indicate the behavior of the channel in an average sense for a particular propagation environment. By using the reference information such as pilots and training symbols in combination with the propagation channel models, the propagation channel statistics may be accurately estimated.
Some channel estimation methods may make assumptions about the propagation channel statistics while other channel estimation methods may use the measured propagation channel statistics from the received signal to adapt the channel estimation to the prevailing propagation channel statistics.